Title :
UKF — Based for sensorless brushless DC motor control
Author :
Haidong Lv ; Guoliang Wei ; Zhugang Ding
Author_Institution :
Dept. of Control Sci. & Eng., Univ. of Shanghai for Sci. & Technol., Shanghai, China
Abstract :
In this paper, a new mathematical model is built according to the characteristics of the BLDC motor and a new filtering algorithm is proposed for sensorless brushless DC (BLDC) motor based on Unscented Kalman Filter(UKF). The proposed UKF algorithm is employed to estimate the speed and rotor position of the BLDC motor only using the measurements of terminal voltages and three-phase currents. In order to observe the drive performance, two simulation examples are given and the feasibility and effectiveness of the UKF algorithm is verified through the simulation results, and the accurate estimate performance is shown in simulation figures.
Keywords :
Kalman filters; brushless DC motors; electric current measurement; estimation theory; nonlinear filters; sensorless machine control; voltage measurement; BLDC motor rotor position estimation; BLDC motor speed estimation; UKF; mathematical model; sensorless brushless DC motor control; terminal voltage measurements; three-phase current measurements; unscented Kalman filter; Brushless DC motors; Kalman filters; Mathematical model; Synchronous motors; Torque;
Conference_Titel :
Mechatronics and Control (ICMC), 2014 International Conference on
Print_ISBN :
978-1-4799-2537-7
DOI :
10.1109/ICMC.2014.7231547